Four-dimensional variational data assimilation for inverse modeling of atmospheric methane emissions: Analysis of SCIAMACHY observations

Recent observations from the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instrument aboard ENVISAT have brought new insights in the global distribution of atmospheric methane. In particular, the observations showed higher methane concentrations in the tropics than previously assumed. Here, we analyze the SCIAMACHY observations and their implications for emission estimates in detail using a four-dimensional variational (4D-Var) data assimilation system. We focus on the period September to November 2003 and on the South American continent, for which the satellite observations showed the largest deviations from model simulations. In this set-up the advantages of the 4D-Var approach and the zooming capability of the underlying TM5 atmospheric transport model are fully exploited. After application of a latitude-dependent bias correction to the SCIAMACHY observations, the assimilation system is able to accurately fit those observations, while retaining consistency with a network of surface methane measurements. The main emission increments resulting from the inversion are an increase in the tropics, a decrease in South Asia, and a decrease at northern hemispheric high latitudes. The SCIAMACHY observations yield considerable additional emission uncertainty reduction, particularly in the (sub-)tropical regions, which are poorly constrained by the surface network. For tropical South America, the inversion suggests more than a doubling of emissions compared to the a priori during the 3 months considered. Extensive sensitivity experiments, in which key assumptions of the inversion set-up are varied, show that this finding is robust. Independent airborne observations in the Amazon basin support the presence of considerable local methane sources. However, these observations also indicate that emissions from eastern South America may be smaller than estimated from SCIAMACHY observations. In this respect it must be realized that the bias correction applied to the satellite observations does not take into account potential regional systematic errors, which - if identified in the future - will lead to shifts in the overall distribution of emission estimates

Four-dimensional variational data assimilation for inverse modelling of atmospheric methane emissions: method and comparison with synthesis inversion

A four-dimensional variational (4D-Var) data assimilation system for inverse modelling of atmospheric methane emissions is presented. The system is based on the TM5 atmospheric transport model. It can be used for assimilating large volumes of measurements, in particular satellite observations and quasi-continuous in-situ observations, and at the same time it enables the optimization of a large number of model parameters, specifically grid-scale emission rates. Furthermore, the variational method allows to estimate uncertainties in posterior emissions. Here, the system is applied to optimize monthly methane emissions over a 1-year time window on the basis of surface observations from the NOAA-ESRL network. The results are rigorously compared with an analogous inversion by Bergamaschi et al. (2007), which was based on the traditional synthesis approach. The posterior emissions as well as their uncertainties obtained in both inversions show a high degree of consistency. At the same time we illustrate the advantage of 4D-Var in reducing aggregation errors by optimizing emissions at the grid scale of the transport model. The full potential of the assimilation system is exploited in Meirink et al. (2008), who use satellite observations of column-averaged methane mixing ratios to optimize emissions at high spatial resolution, taking advantage of the zooming capability of the TM5 model

McSCIA: application of the Equivalence Theorem in a Monte Carlo radiative transfer model for spherical shell atmospheres

A new multiple-scattering Monte Carlo 3-D radiative transfer model named McSCIA (Monte Carlo for SCIAmachy) is presented. The backward technique is used to efficiently simulate narrow field of view instruments. The McSCIA algorithm has been formulated as a function of the Earth&apos;s radius, and can thus perform simulations for both plane-parallel and spherical atmospheres. The latter geometry is essential for the interpretation of limb satellite measurements, as performed by SCIAMACHY on board of ESA&apos;s Envisat. The model can simulate UV-vis-NIR radiation. <br><br> First the ray-tracing algorithm is presented in detail, and then successfully validated against literature references, both in plane-parallel and in spherical geometry. A simple 1-D model is used to explain two different ways of treating absorption. One method uses the single scattering albedo while the other uses the equivalence theorem. The equivalence theorem is based on a separation of absorption and scattering. It is shown that both methods give, in a statistical way, identical results for a wide variety of scenarios. Both absorption methods are included in McSCIA, and it is shown that also for a 3-D case both formulations give identical results. McSCIA limb profiles for atmospheres with and without absorption compare well with the one of the state of the art Monte Carlo radiative transfer model MCC++. <br><br> A simplification of the photon statistics may lead to very fast calculations of absorption features in the atmosphere. However, these simplifications potentially introduce biases in the results. McSCIA does not use simplifications and is therefore a relatively slow implementation of the equivalence theorem

Synthesis of PMMA-b-PU-b-PMMA tri-block copolymers through ARGET ATRP in the presence of air

ARGET (activators regenerated by electron transfer) ATRP (atom transfer radical polymerization) has been successfully performed (in flasks fitted with rubber septa without the need for use of Schlenk line) in the presence of limited amount of air and with a very small (370 ppm) amount of copper catalyst together with an appropriate reducing agent Cu(0). Novelty of this work is that the poly(methyl methacrylate)-block-polyurethane-block-poly(methyl methacrylate) triblock copolymers were synthesized for the first time through ARGET ATRP, by using tertiary bromine-terminated polyurethane as a macroinitiator (MBP-PU-MBP), CuBr2 or CuCl2 as a catalyst and N,N,N',N",N"-pentamethyldiethylenetriamine (PMDETA) or 2,2'-bipyridine (Bpy) as a complexing agent. As the polymerization time increases, both the monomer conversion and ln([M]0/[M]) increased and the molecular weight of copolymer increases linearly with increasing conversion. Theoretical number-average molecular weight (Mn, th) of the tri-block copolymers was found to be comparable with number-average molecular weight determined by GPC analyses (Mn, GPC). These results indicate that the formation of the tri-block copolymers was through atom transfer radical polymerization mechanism. 1H and 13C NMR spectral methods were employed to confirm chemical structures of synthesized macroinitiator and tri-block copolymers. Mole percentage of PMMA in the tri-block copolymers was calculated using 1H NMR spectroscopy and was found to be comparable with the GPC results. Additionally, the studies of surface properties (confocal microscopy and SFE) of tri-block copolymer coatings confirmed the presence of MMA segments

Inverse modeling of European CH4 emissions: sensitivity to the observational network

Inverse modeling is widely employed to provide “top-down” emission estimates using atmospheric measurements. Here, we analyze the dependence of derived CH4 emissions on the sampling frequency and density of the observational surface network, using the TM5-4DVAR inverse modeling system and synthetic observations. This sensitivity study focuses on Europe. The synthetic observations are created by TM5 forward model simulations. The inversions of these synthetic observations are performed using virtually no knowledge on the a priori spatial and temporal distribution of emissions, i.e. the emissions are derived mainly from the atmospheric signal detected by the measurement network. Using the European network of stations for which continuous or weekly flask measurements are available for 2001, the synthetic experiments can retrieve the “true” annual total emissions for single countries such as France within 20%, and for all North West European countries together within ~5%. However, larger deviations are obtained for South and East European countries due to the scarcity of stations in the measurement network. Upgrading flask sites to stations with continuous measurements leads to an improvement for central Europe in emission estimates. For realistic emission estimates over the whole European domain, however, a major extension of the number of stations in the existing network is required. We demonstrate the potential of an extended network of a total of ~60 European stations to provide realistic emission estimates over the whole European domain

What can 14 CO measurements tell us about OH?

The possible use of 14CO measurements to constrain hydroxyl radical (OH) concentrations in the atmosphere is investigated. 14CO is mainly produced in the upper atmosphere from cosmic radiation. Measurements of 14CO at the surface show lower concentrations compared to the upper atmospheric source region, which is the result of oxidation by OH. In this paper, the sensitivity of 14CO mixing ratio surface measurements to the 3-D OH distribution is assessed with the TM5 model. Simulated 14CO mixing ratios agree within a few molecules 14CO cm¿3 (STP) with existing measurements at five locations worldwide. The simulated cosmogenic 14CO distribution appears mainly sensitive to the assumed upper atmospheric 14C source function, and to a lesser extend to model resolution. As a next step, the sensitivity of 14CO measurements to OH is calculated with the adjoint TM5 model. The results indicate that 14CO measurements taken in the tropics are sensitive to OH in a spatially confined region that varies strongly over time due to meteorological variability. Given measurements with an accuracy of 0.5 molecules 14CO cm¿3 STP, a good characterization of the cosmogenic 14CO fraction, and assuming perfect transport modeling, a single 14CO measurement may constrain OH to 0.2¿0.3×106 molecules OH cm¿3 on time scales of 6 months and spatial scales of 70×70 degrees (latitude×longitude) between the surface and 500 hPa. The sensitivity of 14CO measurements to high latitude OH is about a factor of five higher. This is in contrast with methyl chloroform (MCF) measurements, which show the highest sensitivity to tropical OH, mainly due to the temperature dependent rate constant of the MCF¿OH reaction. A logical next step will be the analysis of existing 14CO measurements in an inverse modeling framework. This paper presents the required mathematical framework for such an analysis

Sources of uncertainties in modelling black carbon at the global scale

Our understanding of the global black carbon (BC) cycle is essentially qualitative due to uncertainties in our knowledge of its properties. This work investigates two source of uncertainties in modelling black carbon: those due to the use of different schemes for BC ageing and its removal rate in the global Transport-Chemistry model TM5 and those due to the uncertainties in the definition and quantification of the observations, which propagate through to both the emission inventories, and the measurements used for the model evaluation. The schemes for the atmospheric processing of black carbon that have been tested with the model are (i) a simple approach considering BC as bulk aerosol and a simple treatment of the removal with fixed 70% of in-cloud black carbon concentrations scavenged by clouds and removed when rain is present and (ii) a more complete description of microphysical ageing within an aerosol dynamics model, where removal is coupled to the microphysical properties of the aerosol, which results in a global average of 40% in-cloud black carbon that is scavenged in clouds and subsequently removed by rain, thus resulting in a longer atmospheric lifetime. This difference is reflected in comparisons between both sets of modelled results and the measurements. Close to the sources, both anthropogenic and vegetation fire source regions, the model results do not differ significantly, indicating that the emissions are the prevailing mechanism determining the concentrations and the choice of the aerosol scheme does not influence the levels. In more remote areas such as oceanic and polar regions the differences can be orders of magnitude, due to the differences between the two schemes. The more complete description reproduces the seasonal trend of the black carbon observations in those areas, although not always the magnitude of the signal, while the more simplified approach underestimates black carbon concentrations by orders of magnitude. The sensitivity to wet scavenging has been tested by varying in-cloud and below-cloud removal. BC lifetime increases by 10% when large scale and convective scale precipitation removal efficiency are reduced by 30%, while the variation is very small when below-cloud scavenging is zero. Since the emission inventories are representative of elemental carbon-like substance, the model output should be compared to elemental carbon measurements and if known, the ratio of black carbon to elemental carbon mass should be taken into account when the model is compared with black carbon observation

Importance of fossil fuel emission uncertainties over Europe for CO2 modeling: model intercomparison

Inverse modeling techniques used to quantify surface carbon fluxes commonly assume that the uncertainty of fossil fuel CO2 (FFCO2) emissions is negligible and that intra-annual variations can be neglected. To investigate these assumptions, we analyzed the differences between four fossil fuel emission inventories with spatial and temporal differences over Europe and their impact on the model simulated CO2 concentration. Large temporal flux variations characterize the hourly fields (~40 % and ~80 % for the seasonal and diurnal cycles, peak-to-peak) and annual country totals differ by 10 % on average and up to 40 % for some countries (i.e., the Netherlands). These emissions have been prescribed to seven different transport models, resulting in 28 different FFCO2 concentrations fields. The modeled FFCO2 concentration time series at surface sites using time-varying emissions show larger seasonal cycles (+2 ppm at the Hungarian tall tower (HUN)) and smaller diurnal cycles in summer (-1 ppm at HUN) than when using constant emissions. The concentration range spanned by all simulations varies between stations, and is generally larger in winter (up to ~10 ppm peak-to-peak at HUN) than in summer (~5 ppm). The contribution of transport model differences to the simulated concentration std-dev is 2–3 times larger than the contribution of emission differences only, at typical European sites used in global inversions. These contributions to the hourly (monthly) std-dev's amount to ~1.2 (0.8) ppm and ~0.4 (0.3) ppm for transport and emissions, respectively. First comparisons of the modeled concentrations with 14C-based fossil fuel CO2 observations show that the large transport differences still hamper a quantitative evaluation/validation of the emission inventories. Changes in the estimated monthly biosphere flux (Fbio) over Europe, using two inverse modeling approaches, are relatively small (less that 5 %) while changes in annual Fbio (up to ~0.15 % GtC yr-1) are only slightly smaller than the differences in annual emission totals and around 30 % of the mean European ecosystem carbon sink. These results point to an urgent need to improve not only the transport models but also the assumed spatial and temporal distribution of fossil fuel emission inventories

Advances and visions in large-scale hydrological modelling: findings from the 11th Workshop on Large-Scale Hydrological Modelling

Large-scale hydrological modelling has become increasingly wide-spread during the last decade. An annual workshop series on large-scale hydrological modelling has provided, since 1997, a forum to the German-speaking community for discussing recent developments and achievements in this research area. In this paper we present the findings from the 2007 workshop which focused on advances and visions in large-scale hydrological modelling. We identify the state of the art, difficulties and research perspectives with respect to the themes "sensitivity of model results", "integrated modelling" and "coupling of processes in hydrosphere, atmosphere and biosphere". Some achievements in large-scale hydrological modelling during the last ten years are presented together with a selection of remaining challenges for the future